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Berlin: 83

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Berlin safety map and travel context

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Compare Berlin areas using official recorded-theft evidence, with broader travel-safety context and source details.

Safrom's citywide research estimate is 83/100. Higher scores mean safer on the model's scale. Evidence as of . Confidence: C.

What does this area's map cover?

143 areas with estimates. Area evidence as of .

recorded_thefts_per_1000_residents · 2025-01-01 / 2025-12-31.

Official register population denominator differs from the federal census used in the headline PKS rate. Per-resident theft rates are influenced by visitors and commuters. Unlocated incidents remain in city totals and are not assigned to individual areas. The source city total exceeds the sum of published area and unknown rows by one theft; no area value is changed. Theft is a specific property-risk input; no time-of-day or other local risk dimension is inferred. The city score uses national priors. Local theft rates adjust only the property dimension across 143 Bezirksregionen. Derived local dataset is CC BY-SA; retain Polizei Berlin attribution and share-alike. LOR boundaries have their separate CC BY 3.0 attribution.

Download the scored safety layer and calculation evidence (GeoJSON)

Area evidence and limitations

Official register population denominator differs from the federal census used in the headline PKS rate. Per-resident theft rates are influenced by visitors and commuters. Unlocated incidents remain in city totals and are not assigned to individual areas. The source city total exceeds the sum of published area and unknown rows by one theft; no area value is changed. Theft is a specific property-risk input; no time-of-day or other local risk dimension is inferred. The city score uses national priors. Local theft rates adjust only the property dimension across 143 Bezirksregionen. Derived local dataset is CC BY-SA; retain Polizei Berlin attribution and share-alike. LOR boundaries have their separate CC BY 3.0 attribution.

Boundaries: Amt für Statistik Berlin-Brandenburg · Berlin LOR Bezirksregionen, 2023 (CC BY 3.0 (boundaries); CC BY-SA (derived theft dataset)).

Before choosing accommodation

  1. Locate your intended stay on the map and check whether that area has evidence.
  2. Read what drives the local differences. A citywide score and an area estimate answer different questions.
  3. Check current local advice and your transport options separately. These estimates cannot assess a specific hotel, street or time of day.

Citywide evidence

Personal violence
91/100
Property & scams
62/100
Getting around
90/100
Health & rescue
94/100
Conflict & stability
89/100
Disaster & environment
60/100
Infrastructure response
93/100

Official register population denominator differs from the federal census used in the headline PKS rate. Per-resident theft rates are influenced by visitors and commuters. Unlocated incidents remain in city totals and are not assigned to individual areas. The source city total exceeds the sum of published area and unknown rows by one theft; no area value is changed. Theft is a specific property-risk input; no time-of-day or other local risk dimension is inferred. The city score uses national priors. Local theft rates adjust only the property dimension across 143 Bezirksregionen. Derived local dataset is CC BY-SA; retain Polizei Berlin attribution and share-alike. LOR boundaries have their separate CC BY 3.0 attribution.

City sources and their limitations
  • European Commission JRC and INFORM partners · Germany INFORM Mid-2026 component priors

    Natural=4; current conflict intensity=1.1; infrastructure=0.7; access to health care=0.6. Each published 0–10 component is multiplied by ten for the existing research risk scale.; Country humanitarian-risk components are weak priors, not measured Berlin street or individual tourist risks.; European Union, CC BY 4.0; component extraction and research transformation by Safrom.

  • UNODC via UN Statistics Division · Germany homicide 2023 and theft 2022, UN Statistical Yearbook

    Homicide: 0.9 per 100,000 (2023); theft: 1,241.4 per 100,000 (2022). Country observations, not Berlin rates.; Property prior uses the same 2022 UN theft series against France (2,011.4), anchored at the existing France research risk 45: 45 + bounded(10 × log2(rate/reference), ±20). This is an explicit weak model calibration, not an official score.; Recording definitions and reporting propensity differ between countries. This country comparison does not create locally observed risks; geographic-fit confidence is 0.2.

  • European Commission, CARE and national sources · Germany road deaths, 2025 preliminary

    34 deaths per million residents, equivalent to 3.4 per 100,000. Preliminary full-year estimate published 2026-03-24; not Berlin traffic exposure.; European Union, CC BY 4.0; unit conversion and research transformation by Safrom.

  • Polizei Berlin · Berlin recorded theft by Bezirksregion, 2025

    Official register population denominator differs from the federal census used in the headline PKS rate.; Per-resident theft rates are influenced by visitors and commuters.; Unlocated incidents remain in city totals and are not assigned to individual areas. The source city total exceeds the sum of published area and unknown rows by one theft; no area value is changed.; Theft is a specific property-risk input; no time-of-day or other local risk dimension is inferred.; CC BY-SA; Polizei Berlin. Local aggregation and transformation by Safrom; redistribution of the derived dataset must preserve attribution and share-alike.

How Safrom uses sources

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